Automated pick-and-place of single nanoparticle using electrically controlled low-surface energy nanotweezer
Ya-Kun Lyu,
Zuo-Tao Ji,
Tao He,
Zhenda Lu,
Weihua Zhang
Affiliations
Ya-Kun Lyu
College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, MOE Key Laboratory of Intelligent Optical Sensing and Manipulation, Nanjing University, Nanjing 210093, China
Zuo-Tao Ji
College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, MOE Key Laboratory of Intelligent Optical Sensing and Manipulation, Nanjing University, Nanjing 210093, China
Tao He
College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, MOE Key Laboratory of Intelligent Optical Sensing and Manipulation, Nanjing University, Nanjing 210093, China
Zhenda Lu
College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, MOE Key Laboratory of Intelligent Optical Sensing and Manipulation, Nanjing University, Nanjing 210093, China
Weihua Zhang
College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, MOE Key Laboratory of Intelligent Optical Sensing and Manipulation, Nanjing University, Nanjing 210093, China
In this work, we developed electrically controlled nanotweezers, which are capable of picking, moving, and placing a single sub-50 nm particle precisely and repeatably in ambient air. The nanotweezers are made of a fluoride polymer coated conductive atomic force microscope tip. By applying voltages on such a low surface energy tip, one can tune the binding energy between the tip and the nanoparticle up and down and consequently pick and place a nanoparticle with a high success rate (>90%). Moreover, we automated the whole pick-and-place procedure with the help of the computer vision technique, and it allows us to pattern nanoparticles into arbitrary patterns without any manual operation.
